1. Regress poverty on our socialism index. With one more year of socialist history, poverty changes by: percentage points (two digits).
# Estimate regression models.
ols_1 <- lm_robust(data = Dat, formula = poverty ~ socialist)
modelsummary(list("Poverty" = ols_1), # Nicely-formatted table.
             statistic = NULL, # Don't report stat. inference
             gof_map = c("nobs", "r.squared"))
tinytable_jm2nek0xlstierqz37s1
Poverty
(Intercept) 11.618
socialist -0.103
Num.Obs. 145
R2 0.007
  1. Regress poverty on civic and political citizenship rights. With a one unit-increase in citizenship rights, poverty changes by: percentage points (two digits).
# Estimate regression models.
ols_2 <- lm_robust(data = Dat, formula = poverty ~ citizen_rights)
modelsummary(list("Poverty" = ols_2), # Nicely-formatted table.
             statistic = NULL, # Don't report stat. inference
             gof_map = c("nobs", "r.squared")) 
tinytable_eygvlbvqy01rco5vcm4l
Poverty
(Intercept) 27.127
citizen_rights -2.154
Num.Obs. 145
R2 0.189
  1. Which of the two is a better model of the variance of poverty across the world?

  2. Make a scatterplot with civic and political citizenship rights on the Y-axis and socialism as predictor on the X-axis.

ggplot(data = Dat, aes(y = citizen_rights, x = socialist)) +
  geom_text(aes(label = country)) +
  labs(x = "Our socialism index", 
       y = "Freedom House index of citizenship rights") +
  theme_minimal() +
  guides(color = "none")

  1. Regress citizenship rights on socialism. With one more year of socialism, citizenship rights change by:
# Estimate regression models.
ols_3 <- lm_robust(data = Dat, formula = citizen_rights ~ socialist)
modelsummary(list("Citiz. Rights" = ols_3), # Nicely-formatted table.
             statistic = NULL, # Don't report stat. inference
              gof_map = c("nobs", "r.squared")) 
tinytable_hrhxvy89f4djcgffdcyj
Citiz. Rights
(Intercept) 7.862
socialist -0.052
Num.Obs. 145
R2 0.045
  1. Make a regression table that displays all three models. Based on the table, discuss with your neighbor: What do the results suggest about whether there is a freedom-equality trade off?
modelsummary(list("Poverty" = ols_1, "Poverty" = ols_2, "Citiz. Rights" = ols_3), # Nicely-formatted table.
              gof_map = c("nobs", "r.squared")) 
tinytable_b6ysc7qsd3aexa9fzssx
Poverty Poverty Citiz. Rights
(Intercept) 11.618 27.127 7.862
(1.674) (4.290) (0.331)
socialist -0.103 -0.052
(0.079) (0.018)
citizen_rights -2.154
(0.425)
Num.Obs. 145 145 145
R2 0.007 0.189 0.045